1. Luận án có thể được phát triển theo hướng xây dựng mô hình cơ sở dựa vào công nghệ trí tuệ nhân tạo (AI) để nhận diện theo đặc tính riêng lẻ của các yêu cầu đầu vào nhằm đánh giá hiệu năng của hệ thống điện toán đám mây. Từ đó có được mô hình lý thuyết đầy đủ hỗ trợ hoạt động nghiên cứu và triển khai hệ thống điện toán đám mây trong thực tế.
2. Ngoài ra, luận án có thể được phát triển theo hướng cải thiện đồng thời hai tham số: thời gian đáp ứng và thời gian xử lý trên môi trường điện toán đám mây. Đây cũng là một cách tiếp cận rất thiết thực trong bối cảnh bùng nổ trao đổi dữ liệu trên môi trường điện toán đám mây hiện nay.
3. Nghiên cứu cân bằng tải trên mạng lưới vạn vật kết nối (IoT) cũng có thể là một hướng phát triển của luận án khi mà cuộc cách mạng công nghệ 4.0 đang làm thay đổi mọi lĩnh vực trong đời sống hàng ngày, hàng giờ.
DANH MỤC CÁC CÔNG TRÌNH CÔNG BỐ
(CT1)
Tran Cong Hung, Nguyen Khoi, Nguyen Xuan Phi (2013), “Survey traffic
matrix for optimizing network performance”, Cyber Journals:
Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), October Edition, 2013 Volume 3, Issue 10, ISSN 1925-2676, pages 29-35, October 2013, Canada.
Website: http://www.cyberjournals.com/Sep2013.html
(CT2)
Nguyễn Xuân Phi, Trần Công Hùng (2015), “Giải Thuật Phòng Tránh Tình
Trạng Quá Tải Trong Điện Toán Đám Mây”, Proceedings of The 2015
National Conference on Electronics, Communications and Information Technology ECIT 2015, pages 66-70, ISBN: 978-604-67-0635-9, December, 10-11, 2015, Ho Chi Minh City, Viet Nam.
(CT3)
Nguyen Xuan Phi, Tran Cong Hung (2016), “Study the Effect of Parameters
to Load Balancing in Cloud Computing”, International Journal of Computer
Networks & Communications (IJCNC) Vol.8, No.3, May 2016.ISSN:0974- 9322 [Online]; 0975-2293 [Print], DOI: 10.5121/ijcnc.2016.8303, pp.33- 45, SCOPUS, the Australian Research Council (ARC) Journal Ranking,
http://airccse.org/journal/ijc2016.html,
http://aircconline.com/ijcnc/V8N3/8316cnc03.pdf
(CT4)
Nguyen Xuan Phi, Tran Cong Hung (2017), “Load Balancing Algorithm to
Improve Response time on Cloud Computing”, International Journal on Cloud
Computing: Services and Architecture (IJCCSA) Vol. 7, No. 6, December 2017, DOI: 10.5121/ijccsa.2017.7601, pp.1-12,
http://airccse.org/journal/ijccsa/current2017.html, http://aircconline.com/ijccsa/V7N6/7617ijccsa01.pdf
(CT5)
Nguyen Xuan Phi, Cao Trung Tin, Luu Nguyen Ky Thu, Tran Cong Hung (2018), “Proposed Load Balancing Algorithm to Reduce Response time and
Processing time on Cloud Computing”, International Journal of Computer
10.5121/ijcnc.2018.10307, pp.87-98, ISSN 0974-9322 (Online), 0975- 2293 (Print), SCOPUS, http://airccse.org/journal/ijc2018.html,
http://aircconline.com/ijcnc/V10N3/10318cnc07.pdf
(CT6)
Tran Cong Hung, Phan Thanh Hy, Le Ngoc Hieu, Nguyen Xuan Phi,
"MMSIA: Improved Max-Min Scheduling Algorithm for Load Balancing on Cloud Computing", ICMLSC 2019 (Proceedings of The 3rd International Conference on Machine Learning and Soft Computing), pp.60-64 ACM New York, NY, USA @2019
(ISBN: 978-1-4503-6612-0), indexed by Ei Compendex, SCOPUS, Da Lat, Vietnam, January 25-28, 2019,
https://dl.acm.org/citation.cfm?id=3311017
(CT7)
Nguyễn Xuân Phi, Lê Ngọc Hiếu, Trần Công Hùng (2019), “Thuật toán cân bằng tải nhằm giảm thời gian đáp ứng dựa vào ngưỡng thời gian trên điện
toán đám mây”, Tạp chí Khoa học và Công nghệ về Thông tin và Truyền
thông (JSTIC- Journal of Science & Technology on Information and Communications, ISSN: 2525-2224, pp.43-48, 04(CS.01)2018, PTIT, 01/2019
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